#################################################### #### lOAD TEST ### #################################################### vdata = h5py_mat2npy('valid_np/edited/valOb_Crop.mat') vtruths = h5py_mat2npy('valid_np/edited/valGt_Crop.mat') #vdata_mat = spio.loadmat('test_np_noise/obhatGausWeak{}Noise128.mat'.format(level), squeeze_me=True) #vtruths_mat = spio.loadmat('valid_np/obGausN1S128val.mat', squeeze_me=True) #vdata = vdata_mat['obhatGausWeak128'] #vdata = preprocess(vdata, data_channels) #vtruths = preprocess(vtruths_mat['obGausN1S128val'], truth_channels) valid_provider = image_util.SimpleDataProvider(vdata, vtruths) #################################################### #### PREDICT ### #################################################### predicts = [] valid_x, valid_y = valid_provider('full') num = valid_x.shape[0] for i in range(num): print('') print('') print('************* {} *************'.format(i))
""" #mat_loader.load_from_net(DS='elips') #-- Training Data --# train_data_path = 'data/train_elips.mat' test_data_path = 'data/test_elips.mat' download_elipse_dataset(train_data_path, test_data_path) data_train, label_train = get_data_from_file(mat_file=train_data_path) data_test, label_test = get_data_from_file(mat_file=test_data_path) #data_channels = 1#data.shape[2] #data = preprocess(data, data_channels) # 4 dimension -> 3 dimension if you do data[:,:,:,1] #label = preprocess(label, truth_channels) data_provider = image_util.SimpleDataProvider(data_train, label_train) valid_provider = image_util.SimpleDataProvider(data_test, label_test) #-- Validating Data --# #vdata_mat = spio.loadmat('valid_np/obhatGausWeak128val_40.mat', squeeze_me=True) #vtruths_mat = spio.loadmat('valid_np/obGausWeak128val_40.mat', squeeze_me=True) # vdata = vdata_mat['obhatGausWeak128val'] # vdata = preprocess(vdata, data_channels) # vtruths = preprocess(vtruths_mat['obGausWeak128val'], truth_channels) #################################################### #### NETWORK ### #################################################### """ here we specify the neural network.